Weakly Supervised Object Localization (WSOL) obtains the localization of objects only with the image-level labels. Most WSOL methods extract activated regions of feature maps, which is called Class Activation Map (CAM) [1]}. It employs a global average pooling (GAP) layer to preserve the spatial information of the feature maps and extracts the spatial region of the feature responses from the last convolutional feature map. Later, Grad-CAM [2]} is proposed to simplify CAM, which extracts the heatmap from any convolutional feature map.
